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Rainfall redistribution in a tropical forest: Spatial and temporal patterns

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dc.contributor.author Zimmerman, Alexander en
dc.contributor.author Zimmermann, Beate en
dc.contributor.author Elsenbeer, Helmut en
dc.date.accessioned 2011-02-16T18:28:37Z
dc.date.available 2011-02-16T18:28:37Z
dc.date.issued 2009
dc.identifier.citation Zimmerman, Alexander, Zimmermann, Beate, and Elsenbeer, Helmut. 2009. "<a href="https%3A%2F%2Frepository.si.edu%2Fhandle%2F10088%2F12255">Rainfall redistribution in a tropical forest: Spatial and temporal patterns</a>." <em>Water Resources Research</em>. 45:W11413&ndash;W11413. <a href="https://doi.org/10.1029/2008WR007470">https://doi.org/10.1029/2008WR007470</a> en
dc.identifier.issn 0043-1397
dc.identifier.uri http://hdl.handle.net/10088/12255
dc.description.abstract The investigation of throughfall patterns has received considerable interest over the last decades. And yet, the geographical bias of pertinent previous studies and their methodologies and approaches to data analysis cast a doubt on the general validity of claims regarding spatial and temporal patterns of throughfall. We employed 220 collectors in a 1-ha plot of semideciduous tropical rain forest in Panama and sampled throughfall during a period of 14 months. Our analysis of spatial patterns is based on 60 data sets, whereas the temporal analysis comprises 91 events. Both data sets show skewed frequency distributions. When skewness arises from large outliers, the classical, nonrobust variogram estimator overestimates the sill variance and, in some cases, even induces spurious autocorrelation structures. In these situations, robust variogram estimation techniques offer a solution. Throughfall in our plot typically displayed no or only weak spatial autocorrelations. In contrast, temporal correlations were strong, that is, wet and dry locations persisted over consecutive wet seasons. Interestingly, seasonality and hence deciduousness had no influence on spatial and temporal patterns. We argue that if throughfall patterns are to have any explanatory power with respect to patterns of near-surface processes, data analytical artifacts must be ruled out lest spurious correlation be confounded with causality; furthermore, temporal stability over the domain of interest is essential. en
dc.relation.ispartof Water Resources Research en
dc.title Rainfall redistribution in a tropical forest: Spatial and temporal patterns en
dc.type Journal Article en
dc.identifier.srbnumber 80903
dc.identifier.doi 10.1029/2008WR007470
rft.jtitle Water Resources Research
rft.volume 45
rft.spage W11413
rft.epage W11413
dc.description.SIUnit STRI en
dc.citation.spage W11413
dc.citation.epage W11413


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